Disintegration of Gaussian measures and average-case optimal algorithms

Vaja Tarieladze; Nicholas Vakhania

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Disintegration of Gaussian measures and average-case optimal algorithms

机译：高斯测度的分解与平均情形最优算法

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摘要

It is shown that a Gaussian measure in a given infinite-dimensional Banach space always admits an essentially unique Gaussian disintegration with respect to a given continuous linear operator. This covers a similar statement made earlier in [Lee and Wasilkowski, Approximation of linear functionals on a Banach space with a Gaussian measure, J. Complexity 2(1) (1986) 12-43.] for the case of finite-rank operators.

机译：结果表明，对于给定的连续线性算子，在给定的无穷维Banach空间中的高斯测度始终允许本质上唯一的高斯分解。对于早期的有限秩算子，这涉及[Lee和Wasilkowski，用高斯测度在Banach空间上线性函数的逼近，J。Complexity 2（1）（1986）12-43。]中所作的类似陈述。

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来源
《Journal of complexity》 |2007年第6期|p.851-866|共16页
作者
Vaja Tarieladze; Nicholas Vakhania;
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作者单位

Department of Stochastic Processes and Applied Statistics, Niko Muskhelishvili Institute of Computational Mathematics, Tbilisi 0193, Georgia;

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原文格式 PDF
正文语种 eng
中图分类数理科学和化学;
关键词
regular conditional probability; disintegration; gaussian measure in banach space; average-case optimal algorithm;

机译：规则条件概率;分解;Banach空间中的高斯测度;平均情形最优算法;

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Disintegration of Gaussian measures and average-case optimal algorithms

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